Comparing climate change indices between a northern (arid) and a southern (humid) basin in Mexico during the last decades

Climate change indices between a northern and a southern basin in Mexico

Comparing climate change indices between a northern (arid) and a southern (humid) basin in Mexico during the last decadesClimate change indices between a northern and a southern basin in MexicoMartín José Montero-Martínez et al.

It is a matter of current study to determine potential
climate changes in different parts of the world, especially in regions like
a basin which has the potential to affect socioeconomic and environmental
issues in a defined area. This study provides a comparison between several
climate change indices trends of two very different basins in Mexico, one
located in the northern arid region (the Conchos River basin) and the other
in the southern humid area (the Usumacinta River basin). First, quality
control, homogenization, and completion of the missing data were applied
before calculating the climate change indices and their respective trends
for the combined period 1961–1994. A clear warming signal was found for the
two basins in addition to an increment in the DTR, in agreement with other
studies in Mexico. Also, the Conchos River basin was found to be more humid
and the Usumacinta River basin drier, in accordance to a supposed seesaw
behavior indicated in previous analysis.

The Conchos River basin (hereinafter CRB) is located at the northern part of
Mexico and covers an area around 72 000 km2 and its range of altitudes
goes from 1000 to almost 2500 m, most of the region is enclosed within an
arid area with a total annual precipitation ranging from 200 to 850 mm. This
basin is important because it is transboundary, and plays a crucial role in
the Mexico-USA Water Treaty (signed in 1944) and also because of its
relevance to the agricultural and livestock issues. In contrast, the
Usumacinta River basin (hereinafter URB) covers around 31 000 km2 (only
in Mexico) and is confined to a tropical humid area with a total annual
precipitation from 1300 to 3200 mm, and terrain altitudes range from 0 to
2000 m (Fig. 1). The Usumacinta River is the largest one in Mexico and it
represents a key part in the biodiversity and economy of one of the less
developed regions in Mexico; furthermore it drains over the Lacandon region,
the largest rainforest in the country.

The ETCCDI has been coordinating an international effort to develop,
calculate, and analyze a suite of indices so that individuals, countries,
and regions can calculate the indices in exactly the same way such that
their analyses will fit adequately into the global picture (Karl et al.,
1999; Peterson, 2005). The goal in this work is to calculate those indices
over the two basins mentioned above and have a preliminary examination of
the possible consequences of global warming in this part of the world.

Figure 1Location and altitudes (m a.s.l.) of the Conchos River basin (CRB)
and the Usumacinta River basin (URB) in Mexico and their corresponding climate
stations (110 for CRB and 67 for URB).

Unfortunately for Mexico, like in many parts of the world, there is a lack
of quantity and quality in the climate data, which translates in very few
studies related to trends and evidence of climate change in the country
(Redmond and Abatzoglou, 2014). Some of those studies have shown that the
Diurnal Temperature Range (DTR) – which is itself one of the indices
recommended by ETCCDI – is increasing in the recent past over Mexico, mainly
because the maximum temperatures are warming at a higher rate than the
minimum temperatures (Englehart and Douglas, 2005; Pavia et al., 2009). On
the other hand, by using the Climatic Research Unit (CRU TS 3.1) data,
Redmond and Abatzoglou (2014) found that the 1990s and the 2000s were the
warmest decades on record for the region. In addition, Easterling et al. (2000)
showed that all of North America (including Mexico) experienced a
clear increase in heavy precipitation events in recent decades. Mateos et
al. (2016) found, in general, an increase in maximum surface temperature and
the diurnal temperature range (DTR) in 10 watersheds around Mexico. However,
the paper concludes that the land-use and land-cover changes could be the
main drivers of climate change in the region.

On a regional basis, Aguilar et al. (2005) provided the first analysis of
the changes in temperature and precipitation extremes for Central America
and Northern South America, with the URB included. Even though they conclude
that the whole region is clearly warming, for the URB they found both
positive and negative trends for warm days and nights and cold days and
nights, although the warming signal prevailed. For several precipitation
indices, they also found a mixture of both positive and negative trends for
the same region. One interesting analysis that physically connects the two
regions of study here is that of Mendez and Magaña (2009) who found that
frequent droughts in northern Mexico coincide with anomalously humid
conditions over southern Mexico and Central America, and vice versa. The
scope of the present study provides a good opportunity to validate the above
assumption even for the short period of time analyzed here.

The official climate data from CLICOM (CLImatological COMputing) historical
database was used for Mexico. The CRB has a total of 110 climate stations
while URB has 67 distributed as in Fig. 1. CLICOM database for Mexico
usually only has a very basic quality control and it is necessary to apply a
more robust procedure to assure good data quality.

Once climate data compilation was performed, a recommendation from ETCCDI
(http://etccdi.pacificclimate.org/, last access: August 2018) was followed in the sense
to carry on first the data quality control (QC) and the homogenization
procedures before calculating the climate indices for the climate stations
(Zhang and Yang, 2004). However, as a first step, it was decided to choose
those 30-year periods which have the greatest number of climate stations with
at least the 80 % of the data during that period. Those periods resulted
to be 1961–1990 for the CRB (14 stations), and 1965–1994 for the URB
(22 stations). After that, Climatol algorithm (Guijarro, 2013, 2018)
was applied for the quality analysis, homogenization and completion of the
missing data in the data series. Quality analysis is applied to minimize
errors related to incorrect transcribed values in the data records.
Homogenization means the removal of non-climatic changes which could be due
to relocations or changes in the instrumentation. Climatol applies the
Standard Normal Homogeneity Test (SNHT) to detect the breakpoints in the
data series (inhomogeneities) (Alexandersson, 1986).

Once the homogenization and completion of the missing data were finished,
the calculation of the climate change indices was performed with ClimPACT2
software (https://github.com/ARCCSS-extremes/climpact2, last access: August 2018) for all
the 36 stations found for both the CRB and the URB and the results are
presented in the next section.

Figure 2Trends for (a) SU (days yr−1), (b) TNN
(∘C yr−1), and (c) DTR (∘C yr−1) for the
CRB (above) and URB (below) (indices explained in the text). Colors and symbols
are explained in each index. Diamond symbols indicate the trends are statistically
significant up to the 95 % of confidence level.

As mentioned above, the quality analysis and the homogenization processes
were performed by using Climatol. Table 1 shows the breakpoints found in the
selected climate stations from CRB (left) and URB (right) river basins.

Results of the linear trends for 10 (out of 27) climate change indices
recommended by ETCCDI are presented on Table 2 (for the CRB) and Table 3
(for the URB). ClimPACT2 uses Ordinary Least Squares (OLS) regression to
calculate the linear trends. The bold numbers are for those linear trends
that resulted with statistical significance up to the 95 % confidence
level (p-value ≤ 0.05). In general, the trends with statistical
significance were more common in the URB than in the CRB.

On the other hand, the geographical distributions of the linear trends of
six of the ETCCDI indices are shown in Figs. 2 and 3 for the two basins. The
linear trends for the summer days (SU, days when Tmax>25∘C),
the annual coldest daily minimum temperature (TNN), and the mean annual
difference between daily maximum and minimum temperatures (DTR) are shown in Fig. 2.

Table 1The number of breakpoints per station found here for every variable
analyzed: precipitation (Prec), maximum and minimum temperature (Tmax
and Tmin respectively). Stations ID numbers (Sta-ID) are given for
the CRB (left) and for the URB (right). The base period was 1961–1990 for the
CRB and 1965–1994 for the URB.

The trends for SU show exactly 50 % of positive and negative trend values
for the CRB, however, the three significant values are all positive. Also,
the positive values of SU seem to dominate the western part of the basin and
the negative ones the eastern part. On the other hand, positive trends of SU
dominate almost all of the URB and up to 8 significant values were found for
the region, all of them positive. Another interesting index to analyze is
TNN in which all of the trends found for the CRB were positive even with up
to 5 significant high values. For the URB, even though there is a mixture of
positive and negative trends all around the basin much more significant
values were positive (5 compared to only 1 negative). Also, positive trends
dominate the southwestern part of the basin and negative trends the
southeastern part. Finally, it is clear that both basins are dominated by
positive DTR trends. In addition, all of the three significant values are
positive for the CRB and most of them (10 out of 13 significant values) are
also positive for the URB.

For the linear trends related to precipitation climate change indices, Fig. 3
shows the maximum annual number of consecutive wet days (Prec ≥ 1 mm) (CWD);
the annual total precipitation (PRCPTOT); and the annual sum of daily
Prec > 99th percentile (R99P). Positive CWD trends dominate
through most of the south and central part of the basin and all of the
significant trends are also positive. On the other hand, for the URB, both
positive and negative trends are observed for CWD (the same for the
significant trends); while negative trends dominate the eastern part of that
region. As for the trends of R99P, it is shown that negative trends
prevailed for both basins, even though only a few resulted to be
statistically significant and all of them in the URB. Finally, for PRCPTOT
positive trends dominate the CRB (10 out of 14 stations) and negative trends
prevail in the URB (17 out of 22 stations), including two significant high
positive trends for the two northernmost stations of the basin.

It is notable that just 13 % for the CRB and 33 % of the climate
stations for the URB satisfied WMO requirements of having at least 80 % of
the data in a full 30-year climate period. Certainly, this example reflects
the importance to adequately maintain climate stations if we want to
increase our confidence in calculating long-term climate change indices and
trends. Unfortunately, not enough data was available to analyze confidently
the most recent decades (the 1990s and 2000s) which are certainly the
warmest according to global mean records (IPCC, 2014).

However, even with those constraints, the analysis shown here is valuable in
the sense that it provides a valuable set of high-quality climate stations
during the combined period of 1961–1994. Thus, with respect to the surface
temperature climate change indices analyzed here, it is concluded that:

The increase in SU, especially for the URB, is in agreement with a warming
signal and that is corroborated by the relatively high number of significant
positive trends there. For the CRB, all of the three significant values were
positive supporting also a warming signal.

The analysis for TNN, also supports a warming signal in the sense that all
of the stations showed a positive trend for this index in the CRB and, even
though for the URB there was a mixture of positive and negative signals, the
significant values were most of them positive.

In addition, it was found that most of the DTR trends increase for both
basins, meaning a rise in the surface temperature climate extremes. This
result is in agreement with those found by other authors in Mexico
(Englehart and Douglas, 2005; Pavia et al., 2009; Mateos et al., 2016) such
as it was discussed earlier.

From the analysis of the indices related to precipitation, it is concluded that:

The analysis shown for the DTR and PRCPTOT trends seem to support the idea
that the CRB was getting more humid during 1961–1990 period. On the other
hand, the same analysis for the URB (1965-1994) seems to show a region
getting drier. Even though the periods of analysis are not exactly the same,
there is a 25-year similar period (1965–1990) in which the results could be
comparable somehow. In that sense, the above result seems to be in agreement
with Mendez and Magaña (2009) given that they found a kind of dipole
that when the northern part of Mexico is drier the southern part is more humid.

By combining the surface temperature and precipitation trend analysis for
the URB, it was shown a mixture of positive and negative trends for the
whole region such as it was found previously by Aguilar et al. (2005) as
discussed earlier. A possible explanation of those results is that the URB
is a complex topographical area in which different local microclimates could
prevail in relatively closed zones because of the altitude differences.
Another possibility is that the regional climate signal differences could be
directly related to land-use and land-cover changes given that this region
is the one with more diversity in the whole country.

More future analyses are necessary to study the similarities and differences
between these two contrasting areas. For that, it would be necessary to
extend not only more climate indices (such as SPI, SPEI, etc.) but also to
extend the period of analysis to be more certain on the conclusions found here.

As mentioned above, the climate data compiled for this study
was obtained directly from CLICOM. The whole CLICOM database for Mexico can be
accessed online at: http://clicom-mex.cicese.mx/mapa.html (last access:
August 2018). In addition, the original databases and generated products of
this paper are available online: http://gradiente.imta.mx/productos
(last access: August 2018).

MJMM led the research, made calculations and wrote the paper.
JSSS provided key programs for the paper. OPD generated the figures. NIPO and
SCL made calculations for the Usumacinta and Conchos respectively.

This article is part of the special issue “17th EMS Annual
Meeting: European Conference for Applied Meteorology and Climatology 2017”.
It is a result of the EMS Annual Meeting: European Conference for Applied
Meteorology and Climatology 2017, Dublin, Ireland, 4–8 September 2017.

Thanks to the financing granted by the Sectorial Fund for Environmental
Research SEMARNAT-CONACYT, Call S0010-2014-1, through project 249435. Also,
we are very grateful to M. S. Jorge Luis Vázquez on getting the data and
to Israel Torres on some informatics issues.

This study provides a comparison between several climate change indices trends of two very different basins in Mexico, one located in the northern arid region (the Conchos River basin) and the other in the southern humid area (the Usumacinta River basin). A clear warming signal was found for the two basins in addition to an increment in the diurnal temperature range, in agreement with other studies in Mexico. Also, the Conchos basin was found to be more humid and the Usumacinta drier.

This study provides a comparison between several climate change indices trends of two very...